Exploiting workload parallelism for performance and power optimization in Blue Gene

Abstract

Optimizing future supercomputing applications will depend on delivering the best performance for a given power budget. To determine the effect on efficiency of application-scaling parameters, this article analyzes system power and performance measurement results for real-world applications exploiting thread- and data-level parallelism on the Blue Gene/L system. © 2006 IEEE.